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Scheduling Ocean Transportation of Crude Oil

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Author Info

  • Gerald G. Brown

    (Naval Postgraduate School, Monterey, California 93943-5100)

  • Glenn W. Graves

    (University of California, Los Angeles, California 90024)

  • David Ronen

    (Naval Postgraduate School, Monterey, California 93943-5100)

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    Abstract

    A crude oil tanker scheduling problem faced by a major oil company is presented and solved using an elastic set partitioning model. The model takes into account all fleet cost components, including the opportunity cost of ship time, port and canal charges, and demurrage and bunker fuel. The model determines optimal speeds for the ships and the best routing of ballast (empty) legs, as well as which cargos to load on controlled ships and which to spot charter. All feasible schedules are generated, the cost of each is accurately determined and the best set of schedules is selected. For the problems encountered, optimal integer solutions to set partitioning problems with thousands of binary variables have been achieved in less than a minute.

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    File URL: http://dx.doi.org/10.1287/mnsc.33.3.335
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 33 (1987)
    Issue (Month): 3 (March)
    Pages: 335-346

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    Handle: RePEc:inm:ormnsc:v:33:y:1987:i:3:p:335-346

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    Related research

    Keywords: transportation: planning; set partitioning; enumerative methods;

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    Cited by:
    1. Hennig, F. & Nygreen, B. & Christiansen, M. & Fagerholt, K. & Furman, K.C. & Song, J. & Kocis, G.R. & Warrick, P.H., 2012. "Maritime crude oil transportation – A split pickup and split delivery problem," European Journal of Operational Research, Elsevier, vol. 218(3), pages 764-774.
    2. Al-Khayyal, Faiz & Hwang, Seung-June, 2007. "Inventory constrained maritime routing and scheduling for multi-commodity liquid bulk, Part I: Applications and model," European Journal of Operational Research, Elsevier, vol. 176(1), pages 106-130, January.
    3. Bilgen, Bilge & Ozkarahan, Irem, 2007. "A mixed-integer linear programming model for bulk grain blending and shipping," International Journal of Production Economics, Elsevier, vol. 107(2), pages 555-571, June.
    4. Ozelkan, Ertunga C. & D'Ambrosio, Alfred & Teng, S. Gary, 2008. "Optimizing liquefied natural gas terminal design for effective supply-chain operations," International Journal of Production Economics, Elsevier, vol. 111(2), pages 529-542, February.
    5. Sambracos, E. & Paravantis, J. A. & Tarantilis, C. D. & Kiranoudis, C. T., 2004. "Dispatching of small containers via coastal freight liners: The case of the Aegean Sea," European Journal of Operational Research, Elsevier, vol. 152(2), pages 365-381, January.
    6. Fagerholt, Kjetil & Lindstad, Håkon, 2000. "Optimal policies for maintaining a supply service in the Norwegian Sea," Omega, Elsevier, vol. 28(3), pages 269-275, June.
    7. Fagerholt, Kjetil, 2001. "Ship scheduling with soft time windows: An optimisation based approach," European Journal of Operational Research, Elsevier, vol. 131(3), pages 559-571, June.
    8. Fagerholt, Kjetil & Christiansen, Marielle & Magnus Hvattum, Lars & Johnsen, Trond A.V. & Vabø, Thor J., 2010. "A decision support methodology for strategic planning in maritime transportation," Omega, Elsevier, vol. 38(6), pages 465-474, December.
    9. Alizadeh, Amir H. & Talley, Wayne K., 2011. "Vessel and voyage determinants of tanker freight rates and contract times," Transport Policy, Elsevier, vol. 18(5), pages 665-675, September.
    10. Shih, Li-Hsing, 1997. "Planning of fuel coal imports using a mixed integer programming method," International Journal of Production Economics, Elsevier, vol. 51(3), pages 243-249, September.
    11. Amir Alizadeh & Wayne Talley, 2011. "Microeconomic determinants of dry bulk shipping freight rates and contract times," Transportation, Springer, vol. 38(3), pages 561-579, May.

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